Window function: lead/lag over category

Last updated: September 30, 2025

Quick Overview

Use window functions to compute running total partitioned by date.

Confluent

Data Manipulation (SQL/Python)

Data Scientist

Confluent

September 30, 2025

Data Scientist

Onsite

Data Manipulation (SQL/Python)

Hard

2,315 solved

Use window functions to compute running total partitioned by date.

Confluent asks this during the Onsite because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.

What the Interviewer Expects

Solve complex analytical problems with elegant, readable SQL
Optimize queries for large-scale datasets with partitioning and indexing
Use recursive CTEs, lateral joins, and advanced window functions
Design the data model alongside the query solution
Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
Consider the operational aspects: query scheduling, incremental processing

Key Topics to Cover

Data cleaning and transformation

Index optimization and query performance

Aggregate functions and GROUP BY

Date/time manipulation

JOIN types and when to use each

How to Approach This

Clarify the schema and expected output format before writing queries.
Use CTEs (WITH clauses) to break complex queries into readable steps.
Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
For pandas, prefer vectorized operations over row-by-row iteration.

Possible Follow-up Questions

What would you do if this query needs to run every 5 minutes?
How would you handle slowly changing dimensions in this scenario?
How would you handle this if the data was spread across multiple databases?

Sharpen Your Skills on Codemia

Practice similar problems with our interactive workspace, get AI feedback, and track your progress.

Practice SQL Problems

Sample Answer

Problem Understanding

The task involves utilizing SQL window functions to compute a running total of a specific measure (e.g., sales, revenue) partitioned by date. The data likely consists of a table with at least three co...

Approach

Identify the Data: Identify the table containing the relevant columns. Let's assume the table is named sales_data with the columns sale_date, category, and amount.
**Window Function...

Submit Your Answer

Markdown supported

Confluent Data Scientist Interview Guide

Interview process, tips, and preparation timeline